metadata
tags:
- spacy
- token-classification
language:
- multilingual
model-index:
- name: xx_LeetSpeakNER_mstsb_mpnet
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.912373549
- name: NER Recall
type: recall
value: 0.9160452962
- name: NER F Score
type: f_score
value: 0.9142057358
| Feature | Description |
|---|---|
| Name | xx_LeetSpeakNER_mstsb_mpnet |
| Version | 0.0.0 |
| spaCy | >=3.4.3,<3.5.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Usage
### UPDATE INSTALLATION WITH PACKAGE NAME
!pip install "xx_LeetSpeakNER_mstsb_mpnet @ https://huggingface.co/Huertas97/xx_LeetSpeakNER_mstsb_mpnet/resolve/main/xx_LeetSpeakNER_mstsb_mpnet-any-py3-none-any.whl"
# Using spacy.load().
import spacy
nlp = spacy.load("xx_LeetSpeakNER_mstsb_mpnet")
# Importing as module.
import xx_LeetSpeakNER_mstsb_mpnet
nlp = xx_LeetSpeakNER_mstsb_mpnet.load()
Label Scheme
View label scheme (4 labels for 1 components)
| Component | Labels |
|---|---|
ner |
INV_CAMO, LEETSPEAK, MIX, PUNCT_CAMO |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
91.42 |
ENTS_P |
91.24 |
ENTS_R |
91.60 |
TRANSFORMER_LOSS |
396910.59 |
NER_LOSS |
373097.06 |